Deterministic 1D Domain Wall Motion with Nucleation-Free Nature in Sliding Ferroelectric Switching

Inhomogeneous domain nucleation and stochastic motion of the domain wall (DW) during the polarization switching process in conventional ferroelectrics introduce a spectrum of intricate kinetic challenges for the reliable and precise manipulation of polarization states, a prerequisite for many ferroelectric implementations. Combining deep-learning-assisted molecular dynamics simulations, microscopic-scale observations, and device-scale electrical measurements, it reveals that sliding ferroelectrics inherently circumvent these issues, with an intrinsic domain-nucleation-free polarization reversal. Using <a:math xmlns:a="http://www.w3.org/1998/Math/MathML" display="inline"> <a:mrow> <a:mrow> <a:mn>3</a:mn> <a:mi>R</a:mi> </a:mrow> <a:mtext>−</a:mtext> <a:msub> <a:mrow> <a:mi>MoS</a:mi> </a:mrow> <a:mrow> <a:mn>2</a:mn> </a:mrow> </a:msub> </a:mrow> </a:math> as a model system, we demonstrate that DW motion occurs along a well-defined 1D pathway in a collective manner, without domain nucleation. Leveraging this predictable domain dynamics, we demonstrate deterministic multistate polarization switching, achieving remarkable precision and repeatability with a variation coefficient of less than 0.2%, 10 times improved over conventional ferroelectrics. This work provides valuable insights into the unique kinetics of DW motion in sliding ferroelectrics and offers opportunities for ferroelectric multistate devices with ultraprecision control.

Authors

Institutions

Publication Details

Journal
Physical Review X
Published
2026-02-17
DOI
https://doi.org/10.1103/q624-x397
Primary Topic
Ferroelectric and Piezoelectric Materials
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Deterministic 1D Domain Wall Motion with Nucleation-Free Nature in Sliding Ferroelectric Switching

Anonymous
Physical Review X
Ferroelectric and Piezoelectric Materials
article

Deterministic 1D Domain Wall Motion with Nucleation-Free Nature in Sliding Ferroelectric Switching

Anonymous
article en

Abstract

Inhomogeneous domain nucleation and stochastic motion of the domain wall (DW) during the polarization switching process in conventional ferroelectrics introduce a spectrum of intricate kinetic challenges for the reliable and precise manipulation of polarization states, a prerequisite for many ferroelectric implementations. Combining deep-learning-assisted molecular dynamics simulations, microscopic-scale observations, and device-scale electrical measurements, it reveals that sliding ferroelectrics inherently circumvent these issues, with an intrinsic domain-nucleation-free polarization reversal. Using <a:math xmlns:a="http://www.w3.org/1998/Math/MathML" display="inline"> <a:mrow> <a:mrow> <a:mn>3</a:mn> <a:mi>R</a:mi> </a:mrow> <a:mtext>−</a:mtext> <a:msub> <a:mrow> <a:mi>MoS</a:mi> </a:mrow> <a:mrow> <a:mn>2</a:mn> </a:mrow> </a:msub> </a:mrow> </a:math> as a model system, we demonstrate that DW motion occurs along a well-defined 1D pathway in a collective manner, without domain nucleation. Leveraging this predictable domain dynamics, we demonstrate deterministic multistate polarization switching, achieving remarkable precision and repeatability with a variation coefficient of less than 0.2%, 10 times improved over conventional ferroelectrics. This work provides valuable insights into the unique kinetics of DW motion in sliding ferroelectrics and offers opportunities for ferroelectric multistate devices with ultraprecision control.

Physical Review XVol. 16(1)
University of Electronic Science and Technology of China (CN), Nankai University (CN), Westlake University (CN), Institute for Advanced Study (DE)
Openalex Percentile: Top 54%
Ferroelectric and Piezoelectric Materials
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.